code: def get_wmma_intrin_group(
      load_scope: Literal["shared", "shared.dyn"],
      store_scope: Literal["global", "shared", "shared.dyn"],
      in_dtype: str,
      out_dtype: str,
      trans_b: bool,
  ) -> Dict[str, str]:
      """Get a group of intrinsics for wmma tensor core with the given configurations
  
      Parameters
      ----------
      load_scope : Literal["shared", "shared.dyn"]
          The memory scope of the input buffer.
  
      store_scope : Literal["global", "shared", "shared.dyn"]
          The memory scope of the result buffer.
  
      in_dtype : str
          The input data type.
  
      out_dtype : str
          The output data dtype.
  
      trans_b : bool
          Whether the input matrix B is transposed.
  
      Returns
      -------
      ret : Dict[str, str]
          A group of tensor intrinsics.
      """
      assert load_scope in ["shared", "shared.dyn"]
      assert store_scope in ["global", "shared", "shared.dyn"]
      assert in_dtype in ["float16", "int8"]
      assert out_dtype in ["float16", "float32", "int32"]
  
      shape = "16x16x16"
      in_dtype = "f16" if in_dtype == "float16" else "s8"
      out_dtype = (
          "f16"
          if out_dtype == "float16"
          else "f32"
          if out_dtype == "float32"
          else "s32"
      )
      # convert "shared.dyn" to "shared_dyn"
      load_scope = load_scope.replace(".", "_")
      store_scope = store_scope.replace(".", "_")
      trans_a = ""
      trans_b = "_trans" if trans_b else ""
  
      # e.g. wmma_load_16x16x16_f16_a_shared
      load_a_intrin = (
          f"wmma_load_{shape}_{in_dtype}_a{trans_a}_{load_scope}"
      )
      # e.g. wmma_load_16x16x16_f16_b_trans_shared_dyn
      load_b_intrin = (
          f"wmma_load_{shape}_{in_dtype}_b{trans_b}_{load_scope}"
      )
      # e.g. wmma_sync_16x16x16_f16f16f32_trans
      compute_intrin = (
          f"wmma_sync_{shape}_{in_dtype}{in_dtype}{out_dtype}{trans_b}"
      )
      # e.g. wmma_fill_16x16x16_f16
      init_intrin = f"wmma_fill_{shape}_{out_dtype}"
      # e.g. wmma_store_16x16x16_f16_shared_dyn
      store_intrin = f"wmma_store_{shape}_{out_dtype}_{store_scope}"
  
      return {
          "init": init_intrin,
          "load_a": load_a_intrin,
          "load_b": load_b_intrin,
          "compute": compute_intrin,
          "store": store_intrin,
      }
  
imports: from typing import Dict, Optional, Tuple, Literal
  from tvm._ffi import register_func
  from tvm.runtime import convert
  from tvm.script import tir
  from tvm.tir.function import PrimFunc
  from tvm.tir import Cast, IntImm, TensorIntrin
label_desc: Use image node_id 16 for calling a global function with example usage: get_wmma_intrin_group(load_scope, store_scope, in_dtype, out_dtype, trans_b) and returns: dict